3 citations · 10 across the 8 of their papers we have counts for
5 papers · 1 filter
MR Optimized Reconstruction of Simultaneous Multi-Slice Imaging Using Diffusion Model
Ting Zhao, Zhuoxu Cui, Sen Jia +6
Diffusion model has been successfully applied to MRI reconstruction, including single and multi-coil acquisition of MRI data. Simultaneous multi-slice imaging (SMS), as a method fo…
Knowledge-driven deep learning for fast MR imaging: undersampled MR image reconstruction from supervised to un-supervised learning
Shanshan Wang, Ruoyou Wu, Sen Jia +4
Deep learning (DL) has emerged as a leading approach in accelerating MR imaging. It employs deep neural networks to extract knowledge from available datasets and then applies the t…
Deep Manifold Learning for Dynamic MR Imaging
Ziwen Ke, Zhuo-Xu Cui, Wenqi Huang +8
Purpose: To develop a deep learning method on a nonlinear manifold to explore the temporal redundancy of dynamic signals to reconstruct cardiac MRI data from highly undersampled me…
An Unsupervised Deep Learning Method for Multi-coil Cine MRI
Ziwen Ke, Jing Cheng, Leslie Ying +3
Deep learning has achieved good success in cardiac magnetic resonance imaging (MRI) reconstruction, in which convolutional neural networks (CNNs) learn a mapping from the undersamp…
Accelerating MR Imaging via Deep Chambolle-Pock Network
Haifeng Wang, Jing Cheng, Sen Jia +8
Compressed sensing (CS) has been introduced to accelerate data acquisition in MR Imaging. However, CS-MRI methods suffer from detail loss with large acceleration and complicated pa…